Abstract

While many segmentation methods rely heavily in some way on edge
detection, the "Active Contours Without Edges" method by Chan and Vese
ignores edges completely. Instead, the method optimally fits a
two-phase piecewise constant model to the given image. The
segmentation boundary is represented implicitly with a level set
function, which allows the segmentation to handle topological changes
more easily than explicit snake methods.

This article describes the level set formulation of the Chan–Vese
model and its numerical solution using a semi-implicit gradient
descent. We also discuss the Chan–Sandberg–Vese method, a
straightforward extension of Chan–Vese for vector-valued images.